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71 lines
2.7 KiB
Python
71 lines
2.7 KiB
Python
# Copyright (c) 2022 PaddlePaddle Authors. All Rights Reserved.
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#
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# Licensed under the Apache License, Version 2.0 (the "License");
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# you may not use this file except in compliance with the License.
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# You may obtain a copy of the License at
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#
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# http://www.apache.org/licenses/LICENSE-2.0
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#
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# Unless required by applicable law or agreed to in writing, software
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# distributed under the License is distributed on an "AS IS" BASIS,
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# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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# See the License for the specific language governing permissions and
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# limitations under the License.
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from __future__ import absolute_import
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import logging
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from ... import c_lib_wrap as C
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def vis_detection(im_data,
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det_result,
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score_threshold=0.0,
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line_size=1,
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font_size=0.5):
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return C.vision.Visualize.vis_detection(
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im_data, det_result, score_threshold, line_size, font_size)
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def vis_face_detection(im_data, face_det_result, line_size=1, font_size=0.5):
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return C.vision.Visualize.vis_face_detection(im_data, face_det_result,
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line_size, font_size)
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def vis_segmentation(im_data, seg_result):
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return C.vision.Visualize.vis_segmentation(im_data, seg_result)
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def vis_matting_alpha(im_data,
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matting_result,
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remove_small_connected_area=False):
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return C.vision.Visualize.vis_matting_alpha(im_data, matting_result,
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remove_small_connected_area)
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def swap_background_matting(im_data,
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background,
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result,
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remove_small_connected_area=False):
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assert isinstance(
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result,
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C.vision.MattingResult), "The result must be MattingResult type"
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return C.vision.Visualize.swap_background_matting(
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im_data, background, result, remove_small_connected_area)
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def swap_background_segmentation(im_data, background, background_label,
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result):
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assert isinstance(
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result, C.vision.
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SegmentationResult), "The result must be SegmentaitonResult type"
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return C.vision.Visualize.swap_background_segmentation(
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im_data, background, background_label, result)
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def remove_small_connected_area(alpha_pred_data, threshold):
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assert len(alpha_pred_data.shape) == 3, "alpha has a (h, w, 1) shape"
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return C.vision.Visualize.remove_small_connected_area(alpha_pred_data,
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threshold)
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def vis_ppocr(im_data, det_result):
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return C.vision.Visualize.vis_ppocr(im_data, det_result)
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